customerio-deploy-pipeline
Deploy Customer.io integrations to production cloud platforms. Use when deploying to Cloud Run, Vercel, AWS Lambda, or Kubernetes with proper secrets management and health checks. Trigger: "deploy customer.io", "customer.io cloud run", "customer.io kubernetes", "customer.io lambda", "customer.io vercel".
84
82%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is a well-crafted skill description that clearly defines its scope (Customer.io deployment), lists specific target platforms, includes explicit trigger guidance, and provides natural keywords users would use. It follows third-person voice and is concise without unnecessary padding. The explicit trigger terms and 'Use when' clause make it easy for Claude to select this skill appropriately.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions and platforms: deploying to Cloud Run, Vercel, AWS Lambda, Kubernetes, with proper secrets management and health checks. These are concrete, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers both 'what' (deploy Customer.io integrations to production cloud platforms with secrets management and health checks) and 'when' (explicit 'Use when' clause with specific platform triggers, plus a dedicated Trigger section). | 3 / 3 |
Trigger Term Quality | Includes explicit trigger terms that users would naturally say: 'deploy customer.io', 'customer.io cloud run', 'customer.io kubernetes', 'customer.io lambda', 'customer.io vercel'. These cover natural variations across multiple platforms. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive by combining Customer.io specifically with deployment to named cloud platforms. The combination of 'Customer.io' + specific deployment targets creates a clear niche unlikely to conflict with generic deployment or generic Customer.io skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides highly actionable, production-ready deployment configurations across multiple cloud platforms with concrete, executable code throughout. Its main weaknesses are the monolithic structure (all platforms inline rather than split into referenced files) and the lack of a clear overarching workflow explaining which steps are alternatives vs. sequential, plus missing post-deployment validation for non-blue-green paths.
Suggestions
Add a brief overview section clarifying that Steps 1/3/4 are alternative deployment targets (not sequential), and Step 2/5 are additive features applicable to any platform.
Split platform-specific configurations into separate referenced files (e.g., `deploy-cloud-run.md`, `deploy-k8s.md`) to improve progressive disclosure and reduce the monolithic body.
Add explicit post-deployment validation steps for Cloud Run and Kubernetes paths (not just blue-green), such as running the health check endpoint and verifying secrets are accessible.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill covers four deployment platforms plus blue-green deployment and health checks, which is a lot of content. While each section is individually reasonable, the sheer volume (covering Cloud Run, Vercel, Lambda mentioned but not shown, Kubernetes, and blue-green) makes this quite long. Some sections like the full Kubernetes manifest could be referenced externally. The health check endpoint creates a real customer profile for monitoring which is questionable but not a verbosity issue per se. | 2 / 3 |
Actionability | All code examples are concrete, executable, and copy-paste ready: complete GitHub Actions workflow YAML, full TypeScript health check endpoint, complete Vercel serverless function, full Kubernetes deployment manifest, and a working blue-green deployment bash script. Each includes specific commands, configuration values, and proper error handling. | 3 / 3 |
Workflow Clarity | The steps are clearly sequenced and the blue-green deployment script includes explicit health check validation before traffic shifting. However, there's no overall deployment workflow tying the steps together—it's unclear if all steps are needed or if they're alternatives. The deployment checklist is helpful but there's no explicit validation/verification step after the full deployment (e.g., run smoke tests, verify metrics). The blue-green script has good validation but other deployment paths lack similar feedback loops. | 2 / 3 |
Progressive Disclosure | The content is well-structured with clear headers and a logical progression, but it's monolithic—all deployment platform configs are inline rather than split into separate files per platform. For a skill this large, the Kubernetes manifest, Vercel function, and Cloud Run workflow could each be referenced files. References to `customerio-ci-integration` and `customerio-webhooks-events` are good cross-references, but no bundle files exist to support progressive disclosure. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Commit
3a2d27d
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.